Ways an Enterprise Data and AI Strategy Drives Exponential Growth

“The price of light is less than the cost of darkness” – Arthur C. Nielsen

This is one of my favorite quotes because it is simple and yet says so much. But what does it mean? Essentially, it suggests that the effort and cost required to bring transparency and knowledge (“light”) are less than the potential harm of remaining uninformed or in the “dark.”

There are many platitudes about data being the new oil, electricity, or currency of business. These concepts imply a “potential energy” that can be harnessed to bring “light,” but how can you tap into that potential?

A Data and AI Strategy is an actionable set of objectives to enable specific technologies, processes, and people to extract value from data and eliminate darkness, resulting in exponential growth opportunities.

Specifically, five of the top ways an Enterprise Data and AI Strategy can achieve this are:

1. Enhanced Decision-Making

An Enterprise Data and AI Strategy enables organizations to make better, more accurate decisions based on data-driven insights rather than intuition or personal biases. AI can analyze vast amounts of complex data to reveal patterns and trends that humans might miss, leading to more informed strategic choices. This improved decision-making can have a compounding effect on business growth over time.

2. Operational Efficiency and Productivity Gains

AI and data-driven solutions can significantly boost operational efficiency and productivity across the organization. By automating routine tasks and streamlining processes, businesses can handle a much higher volume of work at greater speeds. This increased efficiency allows companies to scale operations rapidly without a proportional increase in costs, driving exponential growth.

3. New Revenue Streams and Business Model Expansion

An effective Enterprise Data and AI Strategy can uncover new revenue opportunities and enable business model expansion. By analyzing vast datasets, companies can identify untapped markets, develop innovative products or services, and create entirely new revenue streams. This ability to continuously innovate and expand the business model is crucial for driving exponential growth in today’s rapidly changing market landscape.

4. Personalized Customer Experiences

AI-powered personalization can dramatically improve customer experiences, leading to increased customer satisfaction, loyalty, and, ultimately, revenue growth. By leveraging data and AI to understand individual customer preferences and behaviors, businesses can tailor their offerings, marketing messages, and interactions to each customer’s specific needs. This level of personalization can drive customer acquisition and retention at scale, fueling exponential growth.

5. Agile Adaptation to Market Changes

An Enterprise Data and AI Strategy enables businesses to quickly adapt to market shifts and emerging opportunities. By continuously analyzing market data and trends, AI systems can provide real-time insights that allow companies to adjust their strategies swiftly. This agility is crucial for maintaining a competitive edge and capitalizing on new opportunities faster than competitors, driving rapid and sustained growth.

Data and AI Strategy Opportunities

While these are five of the most common ways a Data and AI Strategy can drive exponential growth, at Sikich, we generally categorize opportunities into three buckets: make more, spend less, and reduce risk.

A practical Data and AI Strategy should identify and inventory the potential… opportunities made possible by tapping into data and detailing the capabilities required to realize it. But how do you do this?

At Sikich, we have a proven (but always evolving) framework for creating our customers’ business-aligned Data and AI Strategies, including a roadmap for building or enhancing the required capabilities to enable it. The diagram below depicts our approach and framework:

The key to a successful Data & AI Strategy is that it is tied to the core objectives of the business. This is achieved through interviews with key stakeholders and understanding the desired outcomes for both the company as well as them and their team or business unit. However, it is vital that these interviewees clearly understand the intent of the Data and AI Strategy effort, which is achieved through a top-down communication strategy.

It is important to develop a well-thought-out interview script, but also to be fluid in the discussion when needed. A SWOT analysis approach can be an effective model for these interviews. However, this is why having deep business acumen is so important. If they don’t believe you understand their function, then they will temper their responses and potentially hold back important suggestions.

While conducting the business objective interviews, assess the current state of the processes, technologies, and data. This can be achieved through documentation review and working sessions with technology and operations teams. The business objective interviews will also help to identify processes that have an opportunity to improve through AI automation or more actionable insights.

An important aspect is to assess and document the current state of maturity of various personas across the organization. A strategy is only as effective as the change management behind it, so this is a crucial step when developing the roadmap to implement the recommended capabilities of the strategy.

Once the assessment has been completed, the opportunities and use-cases should be compiled and classified across the five (or more) areas discussed above, then scored on the potential gains they might have on revenue, cost optimization, and/or risk reduction. With the opportunities identified, the Data and AI Strategy should then provide a recommended future state across the four dimensions of technology, people (organizational design), process, and data. These recommendations typically fall within two categories: Technology Innovation/Modernization and Business Innovation/Transformation. The diagram above depicts a few of the sub-categories within each of these, such as developing a Customer 360 with Master Data Management or building a Single Version of Truth within a Cloud Lake under Technology, and developing a Data Marketplace (catalog) or leveraging Machine/Deep Learning to automate a business process under Business. An additional crucial element to the success of the strategy is a target model for Data and AI Governance. This is depicted as a foundational component spanning Technology and Business transformations.

With the future state defined, the strategy should detail the gaps of each opportunity across the four dimensions (technology, people, process, and data) so that the level of effort is understood for each new or evolved capability. Finally, ROI can be estimated for each of the recommendations in the future state by comparing the potential gains of the opportunities enabled by the capability against both the costs to implement as well as the opportunity costs associated with not implementing them.

We have found that the light is nearly always less than the cost of darkness.

Lastly, with the new capabilities ordered by ROI and time-to-value, a roadmap to implement the recommended future state solutions and to execute a change management strategy can be developed, with quick wins highlighted as the first opportunities to bring more light into the organization.

Next Steps

Now is the time to illuminate your path to a data-driven future. Take the first step towards transforming your business with our tailored approach. Schedule your exclusive ½ day assessment with our expert Data & AI team today and discover how we can help you achieve your strategic goals with actionable insights and cutting-edge technology. Don’t miss this opportunity to bring more light into your organization and unlock the potential of your data. Contact us now to get started!